000			02323nam a22001577a 4500
020			_a9788131200926
082			_a006.312 _bCOX
100			_aCox, Earl
245			_aFuzzy Modeling And Genetic Algorithms For Data Mining And Exploration
260			_aNew Delhi _bMorgann Kaufmann, _c2005
300			_axxi, 530 p. _c18x24 cm
500			_aFuzzy Modeling and Genetic Algorithms for Data Mining and Exploration is a handbook for analysts, engineers, and managers involved in developing data mining models in business and government. As you’ll discover, fuzzy systems are extraordinarily valuable tools for representing and manipulating all kinds of data, and genetic algorithms and evolutionary programming techniques drawn from biology provide the most effective means for designing and tuning these systems. You don’t need a background in fuzzy modeling or genetic algorithms to benefit, for this book provides it, along with detailed instruction in methods that you can immediately put to work in your own projects. The author provides many diverse examples and also an extended example in which evolutionary strategies are used to create a complex scheduling system. Written to provide analysts, engineers, and managers with the background and specific instruction needed to develop and implement more effective data mining systems Helps you to understand the trade-offs implicit in various models and model architectures Provides extensive coverage of fuzzy SQL querying, fuzzy clustering, and fuzzy rule induction Lays out a roadmap for exploring data, selecting model system measures, organizing adaptive feedback loops, selecting a model configuration, implementing a working model, and validating the final model In an extended example, applies evolutionary programming techniques to solve a complicated scheduling problem Presents examples in C, C++, Java, and easy-to-understand pseudo-code Extensive online component, including sample code and a complete data mining workbench "synopsis" may belong to another edition of this title
504			_aIncluding with reference and index
650			_aFuzzy Modeling, Genetic Algorithm, Distributed Knowledge, Data Mining, Fuzzy System for Business Process, Concept of Fuzzy Logic, Fuzzy SQL, Fuzzy Clustering, Genetic Tuning of Fuzzy Moodels
942			_cBK
999			_c18368 _d18368